# Robot Trajectron: Trajectory Prediction-based Shared Control for Robot Manipulation

arXiv: https://arxiv.org/abs/2402.02499 · HTML: https://mlsanity.com/paper/2402.02499/

## Key facts

- Cited by 7 papers in the map (data through 14 Oct 2026).
- Builds on 7 of its 29 references that are in the map.
- First posted on arXiv 4 Feb 2024.

## Builds on (most cited first, 7 of 7)

- [Social GAN: Socially Acceptable Trajectories with Generative Adversarial Networks](https://mlsanity.com/paper/1803.10892/) (2018)
- [It Is Not the Journey but the Destination: Endpoint Conditioned Trajectory Prediction](https://mlsanity.com/paper/2004.02025/) (2020)
- [Social Attention: Modeling Attention in Human Crowds](https://mlsanity.com/paper/1710.04689/) (2017)
- [Stochastic Trajectory Prediction via Motion Indeterminacy Diffusion](https://mlsanity.com/paper/2203.13777/) (2022)
- [Human Trajectory Prediction via Neural Social Physics](https://mlsanity.com/paper/2207.10435/) (2022)
- [Shared Autonomy via Hindsight Optimization for Teleoperation and Teaming](https://mlsanity.com/paper/1706.00155/) (2017)
- [Context-Aware Trajectory Prediction](https://mlsanity.com/paper/1705.02503/) (2017)

## Built on by (most cited first, 7 of 7)

- [Spatial Memory for Out-of-Vision Manipulation in Vision-Language-Action](https://mlsanity.com/paper/2605.22283/) (2026)
- [Probabilistic Human Intent Prediction for Mobile Manipulation: An Evaluation with Human-Inspired Constraints](https://mlsanity.com/paper/2507.10131/) (2025)
- [DTRT: Enhancing Human Intent Estimation and Role Allocation for Physical Human-Robot Collaboration](https://mlsanity.com/paper/2505.17490/) (2025)
- [Chatting about Conditional Trajectory Prediction](https://mlsanity.com/paper/2604.18126/) (2026)
- [Sparse Compositional Flow Matching by geometric assembly from motion primitives](https://mlsanity.com/paper/2605.23341/) (2026)
- [Agent-Centric Social Trajectory Prediction: A Free Energy Principle Perspective](https://mlsanity.com/paper/2605.25748/) (2026)
- [Assistron: Bayesian Shared Autonomy with Off-the-shelf Vision-Language-Action Models](https://mlsanity.com/paper/2606.23147/) (2026)

## Abstract (arXiv)

We address the problem of (a) predicting the trajectory of an arm reaching motion, based on a few seconds of the motion's onset, and (b) leveraging this predictor to facilitate shared-control manipulation tasks, easing the cognitive load of the operator by assisting them in their anticipated direction of motion. Our novel intent estimator, dubbed the Robot Trajectron (RT), produces a probabilistic representation of the robot's anticipated trajectory based on its recent position, velocity and acceleration history. Taking arm dynamics into account allows RT to capture the operator's intent better than other SOTA models that only use the arm's position, making it particularly well-suited to assist in tasks where the operator's intent is susceptible to change. We derive a novel shared-control solution that combines RT's predictive capacity to a representation of the locations of potential reaching targets. Our experiments demonstrate RT's effectiveness in both intent estimation and shared-control tasks. We will make the code and data supporting our experiments publicly available at https://github.com/mousecpn/Robot-Trajectron.git.